- LocationUSA (Remote)
- Work modeRemote
- TypeFull Time
- Salary$190K/Yr - $220/Yr
- Openings1
About the opportunity
Cognichip is a cutting-edge AI startup redefining how semiconductor chips are designed. Headquartered in Redwood City, California, the company is backed by some of the most respected investors in Silicon Valley. Cognichip's mission is to use AI to dramatically accelerate chip design and verification cycles — reducing years of work into weeks through multi-agent autonomous systems.
What you will do
- Design and implement multi-agent AI workflows that automate complex chip design and verification pipelines end-to-end
Skills and experience required
- 6+ years of experience in software or chip engineering
Full job description
About Cognichip
Cognichip is a cutting-edge AI startup redefining how semiconductor chips are designed. Headquartered in Redwood City, California, the company is backed by some of the most respected investors in Silicon Valley. Cognichip’s mission is to use AI to dramatically accelerate chip design and verification cycles — reducing years of work into weeks through multi-agent autonomous systems. The company is at the intersection of Agentic AI and next-generation semiconductor engineering, and is one of the most exciting places to work at in the deep tech space in 2026.
Role Overview
As a Staff Chip Engineer specializing in Agentic Workflows, you will be a core member of Cognichip’s AI platform team. This is not a traditional chip design role — it sits directly at the intersection of advanced LLM-based automation and hardware engineering. You will architect, build, and deploy multi-agent pipelines that allow AI to autonomously execute complex design tasks: from RTL generation and verification to physical design optimization. Your work will directly shape how AI agents reason and collaborate within chip development workflows.
This role demands a rare, powerful combination of hardware engineering knowledge and modern AI systems expertise. You’ll work in a fast-paced, research-forward environment alongside some of the best engineers in the world, turning state-of-the-art research into production systems.
Key Responsibilities
Design and implement multi-agent AI workflows that automate complex chip design and verification pipelines end-to-end
Build and maintain RAG (Retrieval-Augmented Generation) pipelines leveraging domain-specific chip design knowledge bases and vector databases
Architect multi-agent orchestration systems using LangGraph, LangChain, AutoGen, and CrewAI
Develop and expose REST APIs and microservices that allow AI agents to interface with chip design EDA tools, simulators, and data stores
Collaborate directly with AI researchers and chip architects to translate design requirements into agentic task decompositions
Define and instrument evaluation metrics for agent reliability, correctness, and speed
Participate in code reviews, architecture decisions, and cross-functional planning sessions
Stay up-to-date with emerging Agentic AI research and integrate breakthroughs into the platform
Build automated testing frameworks to validate multi-agent workflows at scale
Contribute to the technical vision and product direction of the AI platform
Required Skills & Qualifications
6+ years of experience in software or chip engineering
Proficiency in Python; experience with at least one LLM orchestration framework (LangChain, LangGraph, CrewAI, AutoGen)
Hands-on experience with vector databases (Pinecone, Weaviate, or Chroma)
Deep understanding of RAG pipeline design and prompt engineering patterns
Strong system design skills with experience building scalable, production-grade AI systems
Experience in EDA tools or semiconductor design flows is a significant advantage
Familiarity with cloud platforms (AWS, GCP, or Azure)
What Makes This Role Unique
You are not just building software — you are building the AI brain that designs the chips of tomorrow. This is a legacy-defining role at a company poised to be one of the most important deep tech startups of the decade. Compensation is top-of-market with meaningful equity upside.
Direct referral network
Why candidate applications stand out
Applications include direct proof-of-work repositories and instructor verification endorsements.
Direct internal referral channels through enterprise partners bypass automated résumé discard filters.
A named placement coordinator preps you for each round and follows up with the hiring partner.
Your academy certificate, capstone projects and mock-interview record travel with the application.
Apply for this role
Apply: Staff Chip Engineer- Agentic Workflow
The placement team reviews every application and forwards shortlisted profiles to the hiring partner with your portfolio evidence attached.